code: def test_dynamic_torch_compile(device):
      conv = MySAGEConv(64, 64).to(device)
      conv = torch.compile(conv, dynamic=True)
  
      optimizer = torch.optim.Adam(conv.parameters(), lr=0.01)
  
      for _ in range(10):
          N = random.randrange(100, 500)
          E = random.randrange(200, 1000)
  
          x = torch.randn(N, 64, device=device)
          edge_index = get_random_edge_index(N, N, E, device=device)
  
          optimizer.zero_grad()
          expected = conv(x, edge_index)
          expected.mean().backward()
          optimizer.step()
  
file_path: pytorch_geometric/test/nn/test_compile_dynamic.py
imports: import random
  import torch
  from torch import Tensor
  from torch_geometric.testing import get_random_edge_index, onlyFullTest, onlyLinux, withCUDA, withPackage
  from torch_geometric.utils import scatter
label_desc: Use image node_id 1 for calling a global function with example usage: test_dynamic_torch_compile(device) without return types